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About the job
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
Our team sits at the architectural core of Google Cloud’s enterprise creative AI strategy. We are the experts transforming generative models into bespoke, high-performance engines for global enterprise customers. By fusing Google’s premier video and image foundation models with proprietary data, we address the industry’s post-training issues from Multimodal Supervised Fine-Tuning (SFT) to Latent Distillation to ensure customers can generate brand-aligned, production-grade media at scale.
The Google Cloud AI Research team addresses AI challenges motivated by Google Cloud’s mission of bringing AI to tech, healthcare, finance, retail and many other industries. We work on a range of unique problems focused on research topics that maximize scientific and real-world impact, aiming to push the state-of-the-art in AI and share findings with the broader research community. We also collaborate with product teams to bring innovations to real-world impact that benefits our customers.
The US base salary range for this full-time position is $147,000-$211,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
Responsibilities
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Write product or system development code to build and scale advanced generative media (e.g., image and video) customization features within the Vertex AI ecosystem.
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Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
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Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback to empower enterprise AI developers.
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Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality for large-scale GPU/TPU clusters.
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Implement solutions in one or more specialized ML areas (e.g., diffusion models or multimodal SFT), utilize ML infrastructure, and contribute to model optimization and data processing for high-fidelity media generation.
Minimum qualifications
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Bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience.
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2 years of experience with software development in one or more programming languages (e.g., Python, C++, Java), or 1 year of experience with an advanced degree.
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1 year of experience with one or more of the following: speech/audio, reinforcement learning, ML infrastructure, or specialization in another ML field (e.g., computer vision, generative modeling).
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1 year of experience with ML infrastructure (e.g., deployment, evaluation, optimization) using Py Torch, JAX, or Tensor Flow.
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Experience analyzing large-scale datasets and utilizing ML pipelines to improve model performance and output quality.
Preferred qualifications
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Master's degree or PhD in Computer Science, Artificial Intelligence, or related technical fields with a focus on Generative AI.
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2 years of experience with data structures and algorithms, specifically applied to optimizing machine learning workloads or high-dimensional data processing.
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Experience in developing or fine-tuning Generative AI Media (e.g., image/video) models, including techniques like Latent Distillation or LoRA adaptation.
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Experience developing accessible technologies or tools that ensure safety within AI-generated content.
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Excellent verbal and written English communication skills, with the ability to translate complex ML concepts into actionable technical strategies for stakeholders.
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About Google

Google specializes in internet-related services and products, including search, advertising, and software.
10,001+
Employees
Mountain View
Headquarters
$1,700B
Valuation
Reviews
3.7
25 reviews
Work-life balance
3.8
Compensation
4.2
Culture
3.4
Career
3.9
Management
2.8
68%
Recommend to a friend
Pros
Excellent compensation and benefits
Smart and talented colleagues
Great perks and work flexibility
Cons
Management and leadership issues
Bureaucracy and slow processes
Constantly changing priorities and reorganizations
Salary Ranges
57,502 data points
Junior/L3
L3
L4
L5
L6
L7
L8
Mid/L4
Principal/L7
Senior/L5
Staff/L6
Director
Junior/L3 · Data Scientist L3
0 reports
$176,704
total per year
Base
-
Stock
-
Bonus
-
$150,298
$203,110
Interview experience
9 interviews
Difficulty
3.4
/ 5
Duration
14-28 weeks
Offer rate
44%
Experience
Positive 0%
Neutral 56%
Negative 44%
Interview process
1
Application Review
2
Online Assessment/Technical Screen
3
Phone Screen
4
Onsite/Virtual Interviews
5
Team Matching
6
Offer
Common questions
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Product Sense
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